We propose to continue the productive operation of the Stanford Psychiatric CRC whose purpose is to foster multidisciplinary collaboration in the search for biological correlates of psychiatric illness. We will test pharmacological agents whose actions relate to specific biological hypotheses of psychopathology. In depression we are measuring catecholamines and serotonin metabolites, pituitary thyrotropin response to thyrotropin releasing hormone (TRH), the cortisol response to dexamethasone and the glucose response to glucose and insulin infusion. We are determining the usefulness of these metabolic tests as predictors of drug-response. We are testing the experimental serotonin reuptake blocker fluoxetine as an antidepressant. In schizophrenia, we are looking for abnormalities in spinal fluid (CSF) catecholamine and serotonin metabolites, CSF levels of endogenous opiate peptides (endorphins), and will look for possible N- or O-methylated indoleamines or phenylethylamines. We are testing apomorphine, gamma-hydroxybutyrate, naloxone and beta-endorphin as potential antipsychotic agents in schizophrenia and mania. In patients with tardive dyskinesia, Huntington's disease, and mania we are testing acetylcholine imbalance hypotheses by administering physostigmine and choline chloride. In patients with senile dementia and age related changes in memory function we will test the possibility that chlolinomimetics can significantly improve long-term memory function by administering physostigmine and choline chloride. We are also using both cross-sectional and longitudinal designs to assess schizophrenic and depressed patients using a battery of event-related brain potentials (ERP's). Cortical excitability, stimulus intensity modulation, and various aspects of attention will be assessed. Brain potentials and clinical data are analyzed cross-sectionally to determine the presence of ERP correlations with diagnostic categories or other clinical variables. The data are analyzed longitudinally to determine if any of the brain potential measures predict outcome or drug-response. Finally, we hope that the correlation of biochemical, physiological and clinical variables will improve our understanding of severe mental illness.